In the last 20 -25 years, business owners have heavily depended on SEO meta keywords in the headers and backlinks, but with AI evolution, now a lot of people prefer to search their queries on AI engines instead of using search engines. Even the Google search engine has been integrated with AI searches, which makes it very difficult for businesses to show up there. Even very few people have knowledge about these searches.

As you all know, these AI searches rely on highly optimised data; their crawlers do not wait too long to fetch the data if your website takes too long to load, or if any JavaScript files take too long or block the AI crawlers, then your website will be omitted from AI searches. So, to overcome this, you need to structure your data as per schema.org, and you also need to whitelist all the AI crawlers in your robots.txt file.

After that, you need to place llm.txt and llm-full.txt; these two files play an active role in your AI searches. In these two files, you have to maintain everything and all the information about your brand so that the data will be consumed by the AI bots and their data will be compare by the AI engines with user queries and recommended your business with user if that matches by query. I have written a detailed case study on this AI visibility. If you really want this in more detail, then read this article by accessing the link below

Blog Post on AI visibility

And if you need expert help on AI visibility, then simply reach us by accessing the contact form below

Contact form

Till the time... happy coding!

In the last 2 months, I continuously audited the website, and when I reached the 1000 milestones then I looked for the common issues that I found on websites. Also, after every audit, I drafted an email to the business and informed them about the issues so they could work on them to improve their website.

I targeted business websites across the US/UK and Canada regions and got the interesting facts about that most businesses have offshore tech teams which is resides in India, Bangladesh and Pakistan. I didn't have the problem with the offshore tech teams but when these teams are treated client as money machine then there will arise and because of this below 3 common issues I found with this business websites.

1. Incompatible with Mobile Devices

I am surprised that, even in 2026, this issue is present with business websites; more than 70% of websites take too much time on mobile devices, not because of the layout issue. This issue is because of the too much heavy images were used in websites without any optimisation because of that those were taking too much time to load on mobile devices also there are some third party javascript relies which constantly blocking the view on mobile devices.

When you think as customer pov no customer wants to stay on websites which takes more than 5 seconds to load. This results business were paying for those clicks which they aren't converted into the sales. To overcome this issue, firstly, developers need to optimise the images they use in the desktop version and also need to use lazy loading to load those images so those image load times will not impact the mobile view. Also, they need to inspect the website in mobile view identify the JavaScript files that are blocking on mobile devices, and need to work on those issue.

If anyone wants to watch a video on these issues, then visit the link below

Youtube Video

2. Basic Security and Compliance Issue

A lot of websites do not have the proper privacy policy, terms and conditions, and cookie consent, which are mandatory nowadays. With the AI revolution, a lot of inexperienced developers have started developing websites, but they didn't add these pages, which will cause legal issues for businesses. Also, a lot of websites did not have the proper entries in .htaccess files and in DNS because their traffic was routed over both HTTP and HTTPS protocols, which shows that even with the AI revolution, everyone can develop websites, but websites that experienced developers develop are different, as experienced developers always follow all the compliance and security issues that were missing with these AI-dependent developers.

3. Not having the proper CTA's and layout

When the website doesn't have the proper visuals CTA's, then it's difficult for the business to generate leads from such websites. Some of the business find out cheap deals with such AI dependent developers which didnt designed there website with proper CTA's which causing these issue. When the business launches the ad campaign, and their target audience lands on such a page where they need to find all the buttons for calls or contact forms, it is very difficult for the business to convert them into leads.

I found that the websites had "call now" as text in green, but there is no call icon and no button styles, which confused customers from where they will get the numbers but in actual those text are working as buttons. This is a sign of inexperienced developers who only copy-paste AI code on websites.

For me, it is possible to audit all the websites in very little time just because of my Chrome extension Affiscope, which is free on the Chrome Web Store. It's specially designed for businesses and inexperienced developers who haven't audited their website. So this tool helps them to audit the website and identify issues on websites so they will work on those issues.

Also, if anyone wants to audit their website with my experience and needs a detailed report with solutions, then they can reach me through my portfolio website. I hope this article will help you all in your daily activities.

Sending raw, unfiltered user input to third-party AI providers creates severe security risks:

• 🔑 Accidental Secret Leaks: API keys, AWS credentials, and OAuth tokens embedded in prompts.

• 👤 PII Exposure: Emails, phone numbers, and IP addresses violating GDPR, HIPAA, or CCPA compliance.

• ⚡ Prompt Injection & Abuse: Malicious payloads exploiting model context windows.

To solve this problem at the middleware layer, I built and published ai-prompt-firewall — an open-source, zero-dependency Node.js and TypeScript library that inspects, sanitizes, and redacts sensitive prompt payloads in real time.

⚡ Key Architectural Features

• 🚀 Zero External Dependencies: Built with native TypeScript/ESM for minimal bundle overhead and ultra-fast execution times.

• 🔍 Comprehensive Pattern Matching: Pre-configured to detect API keys (OpenAI, Anthropic, AWS, Stripe, GitHub, Google API, Slack, Private Keys, Bearer Tokens) and PII (Emails, Phone Numbers, IPv4 Addresses).

• 🎯 Three Enforcement Modes:

  • redact: Automatically obfuscates secrets into clean inline placeholders (e.g., [OPENAI_KEY_REDACTED]).

  • block: Enforces zero-trust isolation by aborting execution when policy violations are detected.

  • warn: Logs findings without mutating the input string for background monitoring.

• 📊 SIEM-Ready Audit Metadata: Exports precise character offsets (startIndex, endIndex, match length) for enterprise security event logging.

• 🏢 Multi-Tenant Architecture: Pre-compile isolated regex registries (createFirewall) supporting custom runtime rules per customer or service context.

📦 Quick Start

1. Installation

Install directly from the public npm registry:

npm install ai-prompt-firewall

2. Standard Prompt Inspection

Here is a simple example scanning a prompt containing a sensitive token:

import { scan } from 'ai-prompt-firewall';

const userPrompt = "Here is my secret key: sk-proj-1234567890abcdef1234567890abcdefABCDEF";

// Execute redaction scan const result = scan(userPrompt, 'redact');

console.log(result.safePrompt); // Output: "Here is my secret key: \[OPENAI\_KEY\_REDACTED\]"

console.log(result.findings); /\* Output: \[ { type: 'OPENAI\_KEY', severity: 'CRITICAL', startIndex: 23, endIndex: 69, matchedSnippetLength: 46 } \] \*/

🛠️ Advanced Usage

% notification % Pro Tip: Pre-compile firewall instances when serving multi-tenant workloads to optimize regex compilation overhead across concurrent requests.

Extending with Custom Patterns

You can pass runtime regex rules directly to detect internal organization codes, badge IDs, or proprietary keys:

import { scan } from 'ai-prompt-firewall';

const customPatterns = {
  INTERNAL_PROJECT_CODE: /PROJ-[A-Z]{3}-\d{4}/g
};

const input = "Confidential project reference: PROJ-XYZ-9876";
const result = scan(input, "redact", { customPatterns });

console.log(result.safePrompt);
// Output: "Confidential project reference: [INTERNAL_PROJECT_CODE_REDACTED]"

Creating Isolated Multi-Tenant Firewalls

import { createFirewall } from 'ai-prompt-firewall';

const tenantFirewall = createFirewall({
  customPatterns: {
    TENANT_BADGE: /BADGE-\d{5}/g
  }
});

const tenantResult = tenantFirewall.scan("Employee badge is BADGE-99887", "block");

if (tenantResult.blocked) {
  console.log("Access denied: Prompt contains restricted badge token.");
}

🔗 Try It Out & Contribute

ai-prompt-firewall is completely open-source and ready for production integration.

• npm Package: npmjs.com/package/ai-prompt-firewall

• GitHub Repository: github.com/GamersStop/ai-prompt-firewall

If you find this project helpful for securing your AI infrastructure, feel free to drop a ⭐️ on GitHub or leave your feedback in the comments below!

To solve this, I decided to build and publish my own open-source package from scratch: universal-form-validator.

🌟 Key Features:

• Zero Dependencies: Keeps your project bundle lightweight and fast.

• Flexible Schemas: Easily handles common validation requirements like strings, strict numbers, emails, dates, and passwords.

• Framework Friendly: Tested and structured to plug smoothly into modern workflows.

📦 Quick Start:

You can install it directly via npm:

Bash

npm i universal-form-validator

🔗 Resources:

• GitHub Repository: universal-form-validator on GitHub

• npm Package: universal-form-validator on npm

I built this to solve a specific workflow problem, and I'd love to hear your thoughts, feedback, or any code contributions if you try it out. Happy coding! 🚀